Grading Policy
This course will employ a “portfolio” grading approach, which considers the quality of the entire portfolio of work submitted, along with commentary from each student about the work that they put into producing their portfolio, and a self-assessment of both the quality and effort put into the production of the portfolio and the entire course, given the stated expectations for the course. Each student will submit a document summarizing the portfolio and including a self-assessment for the course overall and additional possible comments on each assignment. A template for this self-assessment can be found here, which you will include in your portfolio.
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1. The Portfolio will be turned in via Box. ​
2. All documents should be turned in single-spaced and as a PDF document unless indicated otherwise in the assignment description below.​
3. Assignments are due by 11:59 PM on the due date.
Late assignments will be docked 5% per day late that they are turned in.​
4. Failure to comply with the submission instructions outlined below will result in a reduced score on any assignment.
Assignments
A serious reading of the required material for each class session is critical to the structure of this seminar-style course. This is a graduate seminar, and as such, the quality of the discussion hinges on everyone's contribution to the collective analysis, unpacking, and critique of the readings and other material in the course.
You will produce an annotated bibliography of the readings for this course, as well as a set of readings that you cultivate for the lab project. You will write summaries of the central argument for each piece, and at least one point of critique for each reading. The annotated bibliography will include two sections: "Syllabus" and “Lab Project.” In the "Syllabus" section of the annotated bibliography you will choose at least two pieces from each week of the course readings and write the summary/critique for those two pieces. For the "Lab Project" section, over the course of the semester you will find, read, and analyze at least 20 academic sources related to our collective lab project, and write a summary/critique for each of those pieces as well.
You will update the draft of your updated annotated bibliography each week to Box, and you will turn in the complete annotated bibliography at the end of the class (due the last day of class).
Format: The annotated bibliography will list at the top of the first page the TOTAL page count for all of the pieces included in the bibliography (summed together) which you have actually read, and the TOTAL number of pieces read, as well as the average reading score across all pieces (see below).
For each piece in the bibliography you will give 1) the full citation for each source you read in Chicago Author-Date citation format (see http://www.chicagomanualofstyle.org/tools_citationguide.html), 2) a reading score (on the scale described below) for how thoroughly you read the piece, 3) the total number of pages in the piece, 4) the summary paragraph(s), and 5) the short critique paragraph(s). Upload the drafts (on a weekly basis) and the final copy to your personal Box folder for the course. A template for what this bibliography should look like can be found here.
For the reading scores for each piece, please honestly report the depth with which you engaged the piece on this scale:
3-I have read deeply and thoughtfully, and I feel like I have a good grasp of the theoretical or ethnographic narrative in this piece, and I have some well- thought questions and/or critiques of the piece that relate to my work.
2-I did a decent skim of the piece, and I think I at least read over the main points enough to engage to some degree with the main ideas vis-á-vis my project.
1-I looked at it superficially, but maybe only understand a point or two, since I didn't really get to reading it through thoroughly.
Details will be discussed and finalized in the seminar. The components are likely to include original data collection (field notes and recorded media), literature reviews, analytic write-ups, and collaborative analysis and data management with the team.
